Home // GLOBAL HEALTH 2025, The Fourteenth International Conference on Global Health Challenges // View article

Segmented Gait Analysis Using Pressure-Sensing Insoles in a Hemiparetic Patient: A Case Study

Authors:
Tomoko Funayama
Yasutaka Uchida
Eiichi Ohkubo
Ryota Kimura

Keywords: smart insole; rehabilitation; hemiparesis; gait analysis.

Abstract:
Recent technological advancements in wearable devices equipped with a wide range of sensors have enabled the collection of detailed biomechanical data, offering new possibilities for assessing and supporting rehabilitation in both clinical and everyday settings. However, individuals with unstable health conditions or limited physical activity may find it difficult to directly apply analytical methods developed for healthy individuals. This study investigated gait analysis using smart insoles embedded with pressure sensors in four regions of each sole, totaling eight regions, in an individual undergoing rehabilitation for post-stroke hemiparesis. The patient's gait exhibited distinct characteristics compared to that of healthy individuals. Notable features included fluctuating and inconsistent peak and trough values, irregular peak shapes, variable stride times, marked left–right asymmetry, and the absence of distinct peaks during presumed turning phases. Given these differences, conventional analytical methods were not directly applicable; thus, a new analytical approach was developed. Due to the wide variability in peak amplitudes, applying a uniform threshold for peak detection across the entire dataset was not feasible. Additionally, gait involves steady straight walking and variable-speed phases, such as turning, stepping over obstacles, stopping, and swaying—phases that are particularly challenging for individuals with gait impairments. Analyzing the entire walking period under uniform conditions may obscure important gait characteristics. Based on 1.1 times the mode of the stride time, smart insole data were segmented to distinguish between straight and irregular walking phases, followed by the calculation of mean, peak, and post-peak decline values. This approach enabled an objective evaluation of the effectiveness of a gait-assist robot used in rehabilitation, highlighting the clinical potential of smart insole–based gait analysis.

Pages: 18 to 23

Copyright: Copyright (c) IARIA, 2025

Publication date: September 28, 2025

Published in: conference

ISSN: 2308-4553

ISBN: 978-1-68558-294-4

Location: Lisbon, Portugal

Dates: from September 28, 2025 to October 2, 2025